SBCNY Data Mining and Network Analysis

SBCNY Fellow Spotlights
Jayanth Krishnan Roy Song, currently enrolled in the PhD program at Icahn School of Medicine at Mount Sinai, is the first author of a study published in the journal PNAS, titled "ERK Regulation of Phosphodiesterase 4 Enhances Dopamine-stimulated AMPA Receptor Membrane Insertion".
Jayanth Krishnan Jayanth Krishnan, currently enrolled in the Accelerated Physician-Scientist Program (BS/MD) at Rensselaer Polytechnic Institute and Albany Medical College, is a recipient of a 2011 Davidson Scholarship. Jay, who conducted research under the mentorship of SBCNY Investigator Avi Ma'ayan, was the winner in the Engineering category at the Westchester Science and Engineering Fair (WESEF). His project was selected as one of the top eight overall projects which earned him a trip to the Intel International Science and Engineering Fair (ISEF).
[Project] [Davidson Fellow Bio] [Putnam Examiner Article]
Johnson Ho Johnson Ho, City College of New York, Biomedical Engineering major, received the 2011 Barry M. Goldwater Scholarship and was selected as the 2011-2012 Valedictorian of the Grove School of Engineering. Johnson was a summer 2009 SBCNY Fellow who worked under the mentorship of Kevin Costa (MSSM, Department of Medicine) on a project titled: Post-Infarction Left Ventricular Remodeling and the Law of Laplace.
[Project] [CCNY News]
Jayanth Krishnan Sara Wildstein from Queens College (Class of 2010), was one of the recipients of the 2010 Jonas E. Salk Scholarship. She is currently a medical student at the Albert Einstein College of Medicine. Under the mentorship of SBCNY Investigator Eric Sobie during the summer of 2009, Sara's project was titled: Computational modeling of 'leaky' ryanodine receptors and triggered arrhythmias in heart cells.
[Project] [2010 Salk Scholars]
Sumer Undergraduate Program

Data Mining and Network Analysis Course

Data Mining and Network Analysis
BSR6803.01 Systems Biology of Disease and Therapeutics CMC (customized mini-course)

Course Director: Avi Ma'ayan PhD

Course Description
Cell signaling and gene regulatory networks are the focus of biomedical research because such complex systems control cellular behavior. In the past several decades, cell and molecular biologists have accumulated enormous amounts of knowledge about cell regulation; however, many components and details about their interactions, particularly in mammalian cells, are still largely unknown. Hence, we still do not have a holistic understanding of cellular regulation. There is a knowledge gap. However, the rate of data accumulation resulting from emerging high-throughput biotechnologies has the premise to close this knowledge gap, but integrating data from multiple sources to extract real knowledge about regulatory networks and developing new hypotheses and new theories is a major challenge. In this mini-course we will discuss methods used to analyze the topology of biological regulatory networks; we will survey several machine learning approaches and how they are applied to study biological molecular networks; we will discuss papers that combine computational predictions with experimental validation; and use software tools to analyze proteomics and genomics experimental expression data.

Course Schedule Fall 2011

Date Topic Assigned Papers
9/27 Self Organizing Maps PMID: 20202218
10/4 Network Analysis in Systems Biology PMIDs: 10521342, 9623998
10/11 Network Analysis in Systems Biology PMID: 21917719
10/18 Network Analysis in Systems Biology PMID: 21917719
10/25 Decision Tree Classifiers Machine Learning 1:81-106
11/1 Analysis of Microarray and RNA-seq Data
11/8 SVM Classifiers PMID: 18974822
11/22 PCA PMIDs: 20709693, Paper1
11/29 Gene Set Enrichment Analysis PMIDs: 16199517, 21917718
12/6 Unsupervised Clustering of K-Partite Graphs References: Paper1, Paper2

Last Updated: 07/15/2015 17:05:52